Deep Learning for Medical Image Processing
Venkatesan Rajinikanth, E. Priya, Hong Lin, Fuhua Lin · 2020
Deep-learning systems are widely implemented to process a range of medical images. This chapter presents an overview of deep-learning architectures such as AlexNet, VGG-16, and VGG-19, along with its applications in medical image classification. This section discusses the transfer-learning technique and the essential modifications necessary to enhance classification accuracy. A detailed lung CT scan slice classification with the VGG architecture is demonstrated using the image dataset collected from COVID-19 patients. This section presents the experimental results attained using the MATLAB and the PYTHON softwares with the pre-trained AlexNet, VGG-16, and VGG-19.